首页 > 资讯 > EvGen意味着什么 I：筑牢证据生成国家体系的基础

出自识林

2016-04-21 FDA Voice

（译自FDA Voice “What We Mean When We Talk About EvGen Part I: Laying the Foundation for a National System for Evidence Generation” 2016年4月19日，作者：Robert Califf，医师，FDA局长；Rachel Sherman，医师，FDA医药产品和烟草助理副局长。）

整个临床研究产业对目前科学证据生成范式的严重不足的认识愈见深刻，这些科学证据用于支持医疗产品评估和临床护理决策，也用于支持围绕循证基础的相关方法和期望实现现代化的需求。

大家知道，例如，大多数临床实践指导建议并不是基于高品质的证据，通常是从设计合理的随机对照试验得出的。我们也知道，坚持这种高品质证据所支持的标准的结果，对患者而言，意味着更好的产出结果。

有理由相信我们已经到达了一个临界爆发点，之前相互分割的的“孤岛式”工作努力，现在可以相互衔接到一起，打造证据生成（EvGen）国家体系。在这一系列博文的首篇中，从两个基本概念 — 互操作性（interoperability）和连通性，（connectivity）开始，审视构建这样一个国家体系所需的要素。

互操作性

简单地讲，互操作性指不同的人群使用的不同的系统，由于共享标准和路径，这些系统可用于一个共同目的用途的理念。举一个例子：现代列车铁轨在轨距和其它规格方面使用共同达成的标准，从而使许多不同种类的车辆可以安全使用轨道系统。

以类似的方式，应用通用数据标准和定义的证据生成国家体系，可铺就通往实现生物医药数据交流重大改进的“专线”。一旦前期投入得以吸收，伴随着数据收集、数据管护和共享的标准化路径，患者、消费者、专业团体、支付方、医药产品行业和卫生体系都将从提高效率和降低成本中潜在获益。之后，随着这些标准就位，可以专注于生成可用知识，而不只是简单地管理数据。

连通性

在构建证据生成国家体系中，建立可互操作的系统是关键的一步。一个同等重要的步骤，是使得产生数据的很多团体之间，例如患者、临床医生、医院系统、医疗保险机构，能够协同合作。证据源于通常源自许多不同来源或环境的高品质数据。我们可以创建一个互联直通的环境，充分利用所有可用数据为重要公共卫生问题提供答案。这种网络的一个决定性特征，是按需要充分利用针对不同任务的所有可用数据，使得网络具备集成整合输入和输出数据间的复杂关系的能力。与互可操作性标准一起，基于这些原则的证据生成国家体系将能够生成非常巨量的数据，并能够实现这些数据在系统组件之间充分流动。

结果如何？研究人员将能够提炼数据，转化为可以最终指导关系到卫生和医疗保健的临床、监管和个人决策制定的可用证据。

这两个核心建构，代表了必须制定并落实到位以支持证据生成国家体系的至关重要的根本骨架。在我们的下一篇博文中，我们将审视能够着手建立和持续改进的这样一个造福于所有利益攸关者的多种方式。

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What We Mean When We Talk About EvGen Part I: Laying the Foundation for a National System for Evidence Generation
Posted on April 19, 2016 by FDA Voice
By: Rachel E. Sherman, M.D., M.P.H., and Robert M. Califf, M.D.

Across the clinical research enterprise, there is a growing awareness of serious shortfalls in the current paradigm of generating the scientific evidence that supports medical product evaluation and clinical care decisions and the need to modernize methods and expectations surrounding this evidence base.

We know, for instance, that most clinical practice guideline recommendations are not based on high-quality evidence, typically derived from appropriately designed randomized controlled trials. We also know that adherence to standards supported by such high-quality evidence results in better outcomes for patients.

There is reason to believe that we’ve arrived at a tipping point where previously separate, “siloed” efforts can be linked to create a national system for evidence generation (EvGen). In this first of a series of posts, we’ll take a look at the elements required to build such a national system, beginning with a pair of foundational concepts—interoperability and connectivity.

Interoperability

Put simply, interoperability is the idea that different systems used by different groups of people can be used for a common purpose because those systems share standards and approaches. To take one example: modern train tracks employ agreed-upon standards in terms of track gauge and other specifications so that many different kinds of vehicles can safely use the rail system.

In similar fashion, a national system for evidence generation that applied common data standards and definitions could “lay the track” for significant improvements in the exchange of biomedical data. Patients, consumers, professional groups, payers, the medical products industry, and health systems all stand to benefit from potential gains in efficiency and reductions in cost that would accompany standardized approaches to data collection, curation, and sharing, once up-front investments are absorbed. Then, with these standards in place, effort could be devoted to generating actionable knowledge rather than simply managing data.

Connectivity

Establishing interoperable systems is a critical step in building a national system for evidence generation. An equally important step is to enable collaboration among the many groups that generate data, for example patients, clinicians, hospital systems, health insurance organizations. Evidence is derived from high-quality data that often originates from many different sources or settings. We can create an interconnected environment that leverages all the available data to provide answers to important public health questions. A defining characteristic of such a network is the ability to leverage all available data for different tasks as needed, allowing the network to integrate complex relationships between data input and output. Coupled with interoperable standards, a national system for evidence generation based on these principles will be capable of generating very large quantities of data and enabling those data to flow among system components.

The result? Researchers will be able to distill the data into actionable evidence that can ultimately guide clinical, regulatory, and personal decision-making about health and health care.

These two core constructs represent the essential scaffolding that must be developed and put in place to support a national system for evidence generation. In our next posting, we’ll examine ways we can begin building and continuously improving such a system for the benefit of all stakeholders.